STATISTICS

Statistics



Statistics

Linear Regression

Ho: ERA does not have significant effects on the Wins

H1: ERA have significant effects on Wins

Data Analysis

Model Summaryb

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Durbin-Watson

1

.846a

.716

.695

5.98150

1.812

a. Predictors: (Constant), Batting, ERA

b. Dependent Variable: Wins

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

2437.984

2

1218.992

34.071

.000a

Residual

966.016

27

35.778

Total

3404.000

29

a. Predictors: (Constant), Batting, ERA

b. Dependent Variable: Wins

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

-32.891

40.355

-.815

.422

ERA

-15.514

2.004

-.811

-7.743

.000

Batting

682.070

155.816

.458

4.377

.000

a. Dependent Variable: Wins

Interpretation of Data

In this analysis:

Dependant Variable = X = Wins

Independent Variable = Y = ERP & Batting

The equation formed is shows that whatever value is placed on X will have negative impact by 32% and a value placed on Y will also have negative impact by 15%.

From the results mentioned above ...